I-Corps: Network-based artificial intelligence (AI) model that will enable rapid and detailed diagnosis and treatment recommendations for advanced cardiac disease patients

这个I-Corps项目的更广泛的影响/商业潜力是开发数字干预措施，以检测和提供晚期心脏病的早期治疗建议。通过使用人工智能，可以通过早期检测慢性心脏病的轨迹来解决美国最紧迫的医疗负担之一。因此，这项技术将实现多种应用，包括但不限于减少医疗保健相关成本、慢性病负担、专家护理缺口和治疗时间。这项拟议的技术可能会带来一个软件作为数字治疗的新时代，这是传统上为非慢性疾病保留的领域。 该I-Corps项目基于使用神经网络模型开发的软件平台，该模型利用生物标志物与临床生命体征的结合。通过自然实验应用分子和临床数据相结合，使人们有可能了解心脏病的状态变化。通过使用深度神经网络学习，拟议的项目目标是通过复制人脑连接并专注于学习状态变化而不是特定于任务的算法，使算法像人类一样思考和理解。先前在心脏移植领域的分子谱分析与临床数据相结合的工作在创建新的子诊断以及新的人工智能指导的治疗优化方案方面取得了可喜的成果。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of digital interventions to detect and deliver early treatment recommendations for advanced cardiac disease. Through the use of artificial intelligence, it is possible address one of the most pressing healthcare burdens in the United States by detecting trajectories of chronic heart disease early. As a result, this technology would enable multiple applications including, but not limited to, reductions in healthcare-related costs, chronic disease burden, specialist care gaps, and time to treatment. This proposed technology may deliver a new era of software as a digital therapeutic, an area traditionally reserved for non-chronic conditions. This I-Corps project is based on the development of a software platform using neural network models that leverage the use of biomarkers coupled with clinical vitals. Combining molecular and clinical data applied through natural experimentation, has made it is possible to understand the state changes of heart disease. Through the use of deep neural network learning, the proposed project goal is to make algorithms think and understand as humans by replicating the human brain connection and focusing on learning state changes rather than task-specific algorithms. Previous work on molecular profiling paired with clinical data within the realm of heart transplantation has yielded promising results in creating new sub-diagnosis as well as new artificial intelligence-guided therapy optimization protocols.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.